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Record W2768604497 · doi:10.1017/ice.2017.212

Outbreak Response and Incident Management: SHEA Guidance and Resources for Healthcare Epidemiologists in United States Acute-Care Hospitals

2017· article· en· W2768604497 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInfection Control and Hospital Epidemiology · 2017
Typearticle
Languageen
FieldHealth Professions
TopicDisaster Response and Management
Canadian institutionsProvidence Health CareDalhousie University
Fundersnot available
KeywordsOutbreakHealth careMedicineMedical emergencyAcute careMEDLINEInfection controlFamily medicineIntensive care medicineVirologyPolitical science

Abstract

fetched live from OpenAlex

This expert guidance document was developed as a resource to provide healthcare epidemiologists working in acute-care hospitals with a high-level overview of incident management for infectious diseases outbreaks and to prepare them to work within an emergency response framework. It addresses how the epidemiologist's skills and expertise apply to scenarios that require enhanced preparedness and response efforts, eg, when pathogens associated with outbreaks are poorly characterized or when outbreaks require additional interventions including, but not limited to, healthcare personnel education, enhanced infection prevention and control measures, added staffing, supplies, and resources, adjustments to clinical and support activities, and external communications. Its recommendations are not pathogen-specific and are meant to apply to a range of potential infectious diseases outbreaks.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.040
GPT teacher head0.418
Teacher spread0.377 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it